摘要
BACKGROUND: Cognitive impairment after stroke associates with various factors, such as age, educational years, etc. Besides concerning about the recovery of limb function after stroke, we should also focus on the rehabilitation of cognition. Moreover, we’d better pay attention to the control of all the risk factors of stroke, and improve the quality of life in stroke patients. OBJECTIVE: To analyze the factors that affect cognitive impairment after stroke. DESIGN: A related factors analysis. SETTINGS: Department of Neurology of Dalian Port Hospital and Dalian Second People’s Hospital. PARTICIPANTS: Totally 148 stroke inpatients were selected from Department of Neurology, Dalian Port Hospital and Dalian Second People’s Hospital from April 2004 to December 2005, including 100 males and 48 females, aging 45-75 years with an average age of (67±8) years; Their educational years ranged 2-10 years with an average of (6.1±3.7) years; The disease course ranged 15-30 days; All were right-handed. Inclusive criteria: All were accorded with the diagnostic standard set by the Fourth National Academic Meeting for Cerebrovascular Disease; Confirmed by CT or MRI; Informed consents were obtained from all the subjects. METHODS: After the disease conditions were stable, the patients were assessed with Wechsler memory scale (WMS) and Wisconsin card sorting test (WCST). WMS included forward and backward recitation of numbers and short-term memory (verbal memory, visual recognition). The number of times for correct and wrong classifications in WCST and the time to complete the trail making tests A and B were recorded. The focal volume, area and layer were recorded at 24 hours after admission. The general data of the patients were recorded, including name, sex, age, educational years, history of hypertension, history of diabetes mellitus. Electroencepalograph (EEG) was examined to record the wave shape, blood lipids were detected, and the cognition related indexes were analyzed with the Pearson correlation analysis. The correlation between cognitive indexes after stroke and the influencing factors were analyzed with multiple linear regression analysis. MAIN OUTCOME MEASURES: ① Correlation between cognitive indexes and imaging indexes; ② Influencing factors for cognitive indexes after stroke. RESULTS: All the 148 stroke patients were involved in the analysis of results. ① Correlation between cognitive indexes and CT indexes: There were obvious negative correlations between numerical symbol and focal layer (r =-0.234, P < 0.05), as well as between verbal memory and the focal area and volume (r =-0.363, -0.279, P < 0.05); Trail making test A had obvious positive correlation with focal area and volume (r =0.256, 0.256, P < 0.05). Results of multiple linear regression analysis: Correct classification was correlated with triglyceride (partial wave and θ wave (partial regression coefficient=0.231-0.908, P < 0.05); Verbal memory was correlated with EEG α wave, focal volume, sex, educational years and diabetes mellitus (partial regression coefficient=0.219-1.017, P < 0.05-0.01). Visual recognition had correlation with educational years and hypertension (partial regression coefficient=0.326, -1.163, P < 0.01). Trail making tests A and B were correlated with focal volume (partial regression coefficient=4.680, -18.561, P < 0.05). CONCLUSION: The factors that affect the cognitive function after stroke include sex, age, educational years, hypertension, diabetes mellitus, triglyceride, EEG wave shape, and the focal area, volume and layer.
BACKGROUND: Cognitive impairment after stroke associates with various factors, such as age, educational years, etc. Besides concerning about the recovery of limb function after stroke, we should also focus on the rehabilitation of cognition. Moreover, we'd better pay attention to the control of all the risk factors of stroke, and improve the quality of life in stroke patients. OBJECTIVE: To analyze the factors that affect cognitive impairment after stroke. DESIGN: A related factors analysis. SETTINGS: Department of Neurology of Dalian Port Hospital and Dalian Second People's Hospital. PARTICIPANTS: Totally 148 stroke inpatients were selected from Department of Neurology, Dalian Port Hospital and Dalian Second People's Hospital from April 2004 to December 2005, including 100 males and 48 females, aging 45-75 years with an average age of (67±8) years; Their educational years ranged 2-10 years with an average of (6.1±3.7) years; The disease course ranged 15-30 days; All were right-handed. Inclusive criteria: All were accorded with the diagnostic standard set by the Fourth National Academic Meeting for Cerebrovascular Disease; Confirmed by CT or MRI; Informed consents were obtained from all the subjects. METHODS: After the disease conditions were stable, the patients were assessed with Wechsler memory scale (WMS) and Wisconsin card sorting test (WCST). WMS included forward and backward recitation of numbers and short-term memory (verbal memory, visual recognition). The number of times for correct and wrong classifications in WCST and the time to complete the trail making tests A and B were recorded. The focal volume, area and layer were recorded at 24 hours after admission. The general data of the patients were recorded, including name, sex, age, educational years, history of hypertension, history of diabetes mellitus. Electroencepalograph (EEG) was examined to record the wave shape, blood lipids were detected, and the cognition related indexes were analyzed with the Pearson correlation analysis. The correlation between cognitive indexes after stroke and the influencing factors were analyzed with multiple linear regression analysis. MAIN OUTCOME MEASURES: ① Correlation between cognitive indexes and imaging indexes; ② Influencing factors for cognitive indexes after stroke. RESULTS: All the 148 stroke patients were involved in the analysis of results. ① Correlation between cognitive indexes and CT indexes: There were obvious negative correlations between numerical symbol and focal layer (r =-0.234, P < 0.05), as well as between verbal memory and the focal area and volume (r =-0.363, -0.279, P < 0.05); Trail making test A had obvious positive correlation with focal area and volume (r =0.256, 0.256, P < 0.05). Results of multiple linear regression analysis: Correct classification was correlated with triglyceride (partial wave and θ wave (partial regression coefficient=0.231-0.908, P < 0.05); Verbal memory was correlated with EEG α wave, focal volume, sex, educational years and diabetes mellitus (partial regression coefficient=0.219-1.017, P < 0.05-0.01). Visual recognition had correlation with educational years and hypertension (partial regression coefficient=0.326, -1.163, P < 0.01). Trail making tests A and B were correlated with focal volume (partial regression coefficient=4.680, -18.561, P < 0.05). CONCLUSION: The factors that affect the cognitive function after stroke include sex, age, educational years, hypertension, diabetes mellitus, triglyceride, EEG wave shape, and the focal area, volume and layer.
作者
Xiaofang Chen1, Yueji Sun2, Haiyan Liu1, Yunqiao Ding1, Shujuan Liu1, Jinghua Chen1, Xueying Wang1, Zhenpeng Han3, Fang Qu3 1Department of Neurology, Dalian Port Hospital, Dalian 116015, Liaoning Province, China
2Department of Psychology, Dalian Medical University, Dalian 116023, Liaoning Province, China
3 Department of Rheumatology, Second Affiliated Hospital of Dalian Medical University, Dalian 116023, Liaoning Province, China
4Department of Neurology, Dalian Second People’s Hospital, Dalian 116011, Liaoning Province, China
